idx_split = df_train.shape[0]
df_train = df_train.append(df_test)
NumStr =
["MSSubClass","BsmtFullBath","BsmtHalfBath","HalfBath","BedroomAbvGr","KitchenAbvGr","MoSold","YrSo
ld","YearBuilt","YearRemodAdd","LowQualFinSF","GarageYrBlt"]
for col in NumStr:
df_train[col]=df_train[col].astype(str)
non_ordinal_features = ['LandSlope','Utilities','MSZoning',
'Street','Alley','LotShape','LandContour','LotConfig','Neighborhood','Condition1','Condition2','Bld
gType','HouseStyle', 'RoofStyle','RoofMatl','Exterior1st', 'Exterior2nd','MasVnrType','Foundation',
'BsmtExposure','BsmtFinType1','BsmtFinType2', 'Heating', 'CentralAir', 'Electrical','Functional',
'GarageType','GarageFinish','PavedDrive', 'Fence','MiscFeature','SaleType','SaleCondition',
"MSSubClass","BsmtFullBath","BsmtHalfBath","HalfBath","BedroomAbvGr","KitchenAbvGr","MoSold","YrSol
d","YearBuilt","YearRemodAdd","LowQualFinSF","GarageYrBlt"]
ordinal_features = df_train.select_dtypes(include='object').columns.drop(non_ordinal_features)
dummies = pd.get_dummies(df_train.loc[:,non_ordinal_features], drop_first=True) #для кодировки
non_ordinal_features данных в числа
df_train = pd.concat([df_train,dummies], axis=1) # объединим с дф переделанные данные
df_train = df_train.drop(non_ordinal_features,axis=1) # а старые удалим
C:\Users\enoki\AppData\Local\Temp\ipykernel_10776\2525837929.py:15: FutureWarning: In a future
version, `df.iloc[:, i] = newvals` will attempt to set the values inplace instead of always setting
a new array. To retain the old behavior, use either `df[df.columns[i]] = newvals` or, if columns
are non-unique, `df.isetitem(i, newvals)`